Job Title: AI/ML Senior Lead /Team Lead (More Prefer to FinTech Domain)
Job Level: Senior Level / Team Lead
Report to: Project Specialist / Solution Architect.
Department: Technology -> Acquiring.
Organization: Airpay Payment Services Pvt. Ltd (https://www.airpay.co.in/)
Location: Mumbai, Maharashtra.

Job Summary:

- We are seeking a hands-on AI/ML Team Lead with deep, relevant FinTech experience to lead the design, development, deployment, and lifecycle management of secure, scalable, production-grade AI and machine-learning systems.
- The role will focus on high-impact payments and financial-services use cases such as transaction fraud detection, payment-risk scoring, anomaly detection, customer and merchant risk profiling, credit/risk analytics, transaction monitoring, anti-money-laundering (AML) support, chargeback prediction, and operational intelligence.
- The successful candidate will lead ML model training and evaluation, data-pipeline development, MLOps, system design, production deployment, monitoring, governance, and continuous improvement while ensuring high-quality delivery within committed timelines.

Skills and Experience:

- 6+ years of relevant experience in AI/ML, data science, MLOps, data engineering, risk analytics, or software engineering, including 1–3 years of technical-lead, team-lead, or people-management experience.
- 3+ years of relevant experience in FinTech, payments, banking, lending, insurance, fraud prevention, credit/risk analytics, transaction monitoring, or a comparable regulated financial-services environment.
- Expert-level Python proficiency, including writing clean, tested, maintainable, secure, and performance aware production code. Python is compulsory.
- Practical experience applying ML algorithms to FinTech or risk use cases, including Logistic Regression, Random Forest, XGBoost, LightGBM, CatBoost, Gradient Boosting, decision trees,



anomaly-detection methods such as Isolation Forest, clustering, and ensemble modelling.
- Robust knowledge of tree-based boosting methods—particularly XGBoost, LightGBM, and CatBoost— and Random Forest for tabular transaction, customer, merchant, and risk datasets. These algorithms are commonly valuable for FinTech problems because they model nonlinear feature interactions effectively; however, the candidate must be able to validate models rigorously and balance predictive performance with explainability and operational needs.
- Experience with ML frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, Hugging Face, or equivalent tools.
- Experience developing and validating fraud, risk, anomaly-detection, transaction-monitoring, or other decisioning models, including treatment of severe class imbalance, delayed labels, concept drift, threshold selection, and cost-sensitive trade-offs.
- Ability to evaluate fraud and risk models using more than accuracy, with strong understanding of precision, recall, F1, PR-AUC, ROC-AUC, calibration, false positives/negatives, business loss, operational review capacity, and decision latency.
- Strong MLOps experience, including CI/CD, model/data/feature versioning, experiment tracking, reproducible training, automated testing, deployment pipelines, monitoring, alerting, and retraining workflows.
- Strong hands-on experience with ETL/ELT, streaming, event-driven, or real-time data pipelines; knowledge of data quality, orchestration, observability, and feature consistency between training and serving.




- Strong system-design capability for scalable ML services and platforms, including throughput, low latency scoring, fault tolerance, resilience, security, privacy, maintainability, and cost optimisation.
- Hands-on experience building and deploying Docker-based services and applications.
- Strong working knowledge of Git, including pull requests, code reviews, release management, and collaborative development workflows.
- Required experience with MySQL and PostgreSQL, including SQL, schema design, indexing, query optimisation, data integrity, and secure data-access practices.
- Experience with RAG architectures, vector search/retrieval concepts, LLM integration, prompt design, evaluation, and secure implementation for enterprise knowledge workflows is desirable.
- Experience with MCP, tool integrations, AI agents, or secure and auditable enterprise AI workflows is desirable.
- Go/Golang experience is a strong advantage. Additional programming languages are an added benefit.
- Familiarity with cloud platforms, container orchestration, message queues/streaming systems, observability tools, infrastructure-as-code, and secure deployment practices is desirable.
- Excellent analytical thinking and strong problem-solving skills, with the ability to convert ambiguous payment, fraud, and risk problems into practical, measurable solutions.
- Strong written and verbal communication skills, stakeholder-management capability, and the ability to explain model performance, risks, trade-offs, and limitations to technical and non-technical audiences.
- Demonstrated ownership, attention to detail, adaptability, integrity, and ability to work effectively in a fast-paced, deadline-oriented environment.

Pay: ₹1,409,607.90 - ₹2,400,796.53 per year

Benefits:

- Flexible schedule
- Health insurance
- Provident Fund

Work Location: In person

📌 AI/ML Lead Engineer (India)
🏢 Airpay Payment Services Pvt.Ltd.
📍 India